MonoRes: Automatic and Accurate Estimation of Local Resolution for Electron Microscopy Maps

Tension-induced suppression of allosteric conformational changes coordinates kinesin-1 stepping

Kinesin-1 walks along microtubules by alternating ATP hydrolysis and movement of its two motor domains ("head"). The detached head preferentially binds to the forward tubulin-binding site after ATP binds to the microtubule-bound head, but the mechanism preventing premature microtubule binding while the partner head awaits ATP remains unknown. Here, we examined the role of the neck linker, the segment connecting two heads, in this mechanism. Structural analyses of the nucleotide-free head revealed a bulge just ahead of the neck linker's base, creating an asymmetric constraint on its mobility. While the neck linker can stretch freely backward, it must navigate around this bulge to extend forward. We hypothesized that increased neck linker tension suppresses premature binding of the tethered head, which was supported by molecular dynamics simulations and single-molecule fluorescence assays. These findings demonstrate a tension-dependent allosteric mechanism that coordinates the movement of two heads, where neck linker tension modulates the allosteric conformational changes rather than directly affecting the nucleotide state.

AI-based quality assessment methods for protein structure models from cryo-EM

Cryogenic electron microscopy (cryo-EM) has revolutionized structural biology, with an increasing number of structures being determined by cryo-EM each year, many at higher resolutions. However, challenges remain in accurately interpreting cryo-EM maps. Inaccuracies can arise in regions of locally low resolution, where manual model building is more prone to errors. Validation scores for structure models have been developed to assess both the compatibility between map density and the structure, as well as the geometric and stereochemical properties of protein models. Recent advancements have introduced artificial intelligence (AI) into this field. These emerging AI-driven tools offer unique capabilities in the validation and refinement of cryo-EM-derived protein atomic models, potentially leading to more accurate protein structures and deeper insights into complex biological systems.

Structural insight into PIF6-mediated red light signal transduction of plant phytochrome B

The red/far-red light receptor phytochrome B (phyB) plays essential roles in regulating various plant development processes. PhyB exists in two distinct photoreversible forms: the inactive Pr form and the active Pfr form. phyB-Pfr binds phytochrome-interacting factors (PIFs) to transduce red light signals. Here, we determined the cryo-electron microscopy (cryo-EM) structures of the photoactivated phyB-Pfr‒PIF6 complex, the constitutively active mutant phyBY276H‒PIF6 complex, and the truncated phyBNY276H‒PIF6 complex. In these structures, two parallel phyB-Pfr molecules interact with one PIF6 molecule. Red light-triggered rotation of the PΦB D-ring leads to the conversion of hairpin loops into α helices and the "head-to-head" reassembly of phyB-Pfr N-terminal photosensory modules. The interaction between phyB-Pfr and PIF6 influences the dimerization and transcriptional activation activity of PIF6, and PIF6 stabilizes the N-terminal extension of phyB-Pfr and increases the Pr→Pfr photoconversion efficiency of phyB. Our findings reveal the molecular mechanisms underlying Pr→Pfr photoconversion and PIF6-mediated red light signal transduction of phyB.

An asymmetric nautilus-like HflK/C assembly controls FtsH proteolysis of membrane proteins

The AAA protease FtsH associates with HflK/C subunits to form a megadalton-size complex that spans the inner membrane and extends into the periplasm of E. coli. How this bacterial complex and homologous assemblies in eukaryotic organelles recruit, extract, and degrade membrane-embedded substrates is unclear. Following the overproduction of protein components, recent cryo-EM structures showed symmetric HflK/C cages surrounding FtsH in a manner proposed to inhibit the degradation of membrane-embedded substrates. Here, we present structures of native protein complexes, in which HflK/C instead forms an asymmetric nautilus-shaped assembly with an entryway for membrane-embedded substrates to reach and be engaged by FtsH. Consistent with this nautilus-like structure, proteomic assays suggest that HflK/C enhances FtsH degradation of certain membrane-embedded substrates. Membrane curvature in our FtsH•HflK/C complexes is opposite that of surrounding membrane regions, a property that correlates with lipid scramblase activity and possibly with FtsH's function in the degradation of membrane-embedded proteins.

Structural recognition and stabilization of tyrosine hydroxylase by the J-domain protein DNAJC12

Pathogenic variants of the J-domain protein DNAJC12 cause parkinsonism, which is associated with a defective interaction of DNAJC12 with tyrosine hydroxylase (TH), the rate-limiting enzyme in dopamine biosynthesis. In this work, we characterize the formation of the TH:DNAJC12 complex, showing that DNAJC12 binding stabilizes both TH and the variant TH-p.R202H, associated with TH deficiency. This binding delays their time-dependent aggregation in an Hsp70-independent manner, while preserving TH activity and feedback regulatory inhibition by dopamine. DNAJC12 alone barely activates Hsc70 but synergistically stimulates Hsc70 ATPase activity when complexed with TH. Cryo-electron microscopy supported by crosslinking-mass spectroscopy reveals two DNAJC12 monomers bound per TH tetramer, each embracing one of the two regulatory domain dimers, leaving the active sites available for substrate, cofactor and inhibitory dopamine interaction. Our results also reveal the key role of the C-terminal region of DNAJC12 in TH binding, explaining the pathogenic mechanism of the DNAJC12 disease variant p.W175Ter.

Automated identification of small molecules in cryo-electron microscopy data with density- and energy-guided evaluation

Methodological improvements in cryo-electron microscopy (cryoEM) have made it a useful tool in ligand-bound structure determination for biology and drug design. However, determining the conformation and identity of bound ligands is still challenging at the resolutions typical for cryoEM. Automated methods can aid in ligand conformational modeling, but current ligand identification tools - developed for X-ray crystallography data - perform poorly at resolutions common for cryoEM. Here, we present EMERALD-ID, a method capable of docking and evaluating small molecule conformations for ligand identification. EMERALD-ID identifies 43% of common ligands exactly and identifies closely related ligands in 66% of cases. We then use this tool to discover possible ligand identification errors, as well as previously unidentified ligands. Furthermore, we show EMERALD-ID is capable of identifying ligands from custom ligand libraries of various small molecule types, including human metabolites and drug fragments. Our method provides a valuable addition to cryoEM modeling tools to improve small molecule model accuracy and quality.

Cryo-EM of human rhinovirus reveals capsid-RNA duplex interactions that provide insights into virus assembly and genome uncoating

The cryo-EM structure of the human rhinovirus B14 determined in this study reveals 13-bp RNA duplexes symmetrically bound to regions around each of the 30 two-fold axes in the icosahedral viral capsid. The RNA duplexes (~12% of the ssRNA genome) define a quasi-dodecahedral cage that line a substantial part of the capsid interior surface. The RNA duplexes establish a complex network of non-covalent interactions with pockets in the capsid inner wall, including coulombic interactions with a cluster of basic amino acid residues that surround each RNA duplex. A direct comparison was made between the cryo-EM structure of RNA-filled virions and that of RNA-free (empty) capsids that resulted from genome release from a small fraction of viruses. The comparison reveals that some specific residues involved in capsid-duplex RNA interactions in the virion undergo remarkable conformational rearrangements upon RNA release from the capsid. RNA release is also associated with the asynchronous opening of channels at the 30 two-fold axes. The results provide further insights into the molecular mechanisms leading to assembly of rhinovirus particles and their genome uncoating during infection. They may also contribute to development of novel antiviral strategies aimed at interfering with viral capsid-genome interactions during the infectious cycle.

A proteolytic AAA+ machine poised to unfold protein substrates

AAA+ proteolytic machines unfold proteins before degrading them. Here, we present cryoEM structures of ClpXP-substrate complexes that reveal a postulated but heretofore unseen intermediate in substrate unfolding/degradation. A ClpX hexamer draws natively folded substrates tightly against its axial channel via interactions with a fused C-terminal degron tail and ClpX-RKH loops that flexibly conform to the globular substrate. The specific ClpX-substrate contacts observed vary depending on the substrate degron and affinity tags, helping to explain ClpXP's ability to unfold/degrade a wide array of different cellular substrates. Some ClpX contacts with native substrates are enabled by upward movement of the seam subunit in the AAA+ spiral, a motion coupled to a rearrangement of contacts between the ClpX unfoldase and ClpP peptidase. Our structures additionally highlight ClpX's ability to translocate a diverse array of substrate topologies, including the co-translocation of two polypeptide chains.

Structural basis for α-tubulin-specific and modification state-dependent glutamylation

Microtubules have spatiotemporally complex posttranslational modification patterns. Tubulin tyrosine ligase-like (TTLL) enzymes introduce the most prevalent modifications on α-tubulin and β-tubulin. How TTLLs specialize for specific substrate recognition and ultimately modification-pattern generation is largely unknown. TTLL6, a glutamylase implicated in ciliopathies, preferentially modifies tubulin α-tails in microtubules. Cryo-electron microscopy, kinetic analysis and single-molecule biochemistry reveal an unprecedented quadrivalent recognition that ensures simultaneous readout of microtubule geometry and posttranslational modification status. By binding to a β-tubulin subunit, TTLL6 modifies the α-tail of the longitudinally adjacent tubulin dimer. Spanning two tubulin dimers along and across protofilaments (PFs) ensures fidelity of recognition of both the α-tail and the microtubule. Moreover, TTLL6 reads out and is stimulated by glutamylation of the β-tail of the laterally adjacent tubulin dimer, mediating crosstalk between α-tail and β-tail. This positive feedback loop can generate localized microtubule glutamylation patterns. Our work uncovers general principles that generate tubulin chemical and topographic complexity.

An asymmetric nautilus-like HflK/C assembly controls FtsH proteolysis of membrane proteins

FtsH, a AAA protease, associates with HflK/C subunits to form a megadalton complex that spans the inner membrane and extends into the periplasm of E. coli. How this complex and homologous assemblies in eukaryotic organelles recruit, extract, and degrade membrane-embedded substrates is unclear. Following overproduction of protein components, recent cryo-EM structures reveal symmetric HflK/C cages surrounding FtsH in a manner proposed to inhibit degradation of membrane-embedded substrates. Here, we present structures of native complexes in which HflK/C instead forms an asymmetric nautilus-like assembly with an entryway for membrane-embedded substrates to reach and be engaged by FtsH. Consistent with this nautilus-like structure, proteomic assays suggest that HflK/C enhances FtsH degradation of certain membrane-embedded substrates. The membrane curvature in our FtsH•HflK/C complexes is opposite that of surrounding membrane regions, a property that correlates with lipid-scramblase activity and possibly with FtsH's function in the degradation of membrane-embedded proteins.

Structural basis for an early stage of the photosystem II repair cycle in Chlamydomonas reinhardtii

Photosystem II (PSII) catalyzes water oxidation and plastoquinone reduction by utilizing light energy. It is highly susceptible to photodamage under high-light conditions and the damaged PSII needs to be restored through a process known as the PSII repair cycle. The detailed molecular mechanism underlying the PSII repair process remains mostly elusive. Here, we report biochemical and structural features of a PSII-repair intermediate complex, likely arrested at an early stage of the PSII repair process in the green alga Chlamydomonas reinhardtii. The complex contains three protein factors associated with a damaged PSII core, namely Thylakoid Enriched Factor 14 (TEF14), Photosystem II Repair Factor 1 (PRF1), and Photosystem II Repair Factor 2 (PRF2). TEF14, PRF1 and PRF2 may facilitate the release of the manganese-stabilizing protein PsbO, disassembly of peripheral light-harvesting complexes from PSII and blockage of the QB site, respectively. Moreover, an α-tocopherol quinone molecule is located adjacent to the heme group of cytochrome b559, potentially fulfilling a photoprotective role by preventing the generation of reactive oxygen species.

Molecular mechanism of the ischemia-induced regulatory switch in mammalian complex I

Respiratory complex I is an efficient driver for oxidative phosphorylation in mammalian mitochondria, but its uncontrolled catalysis under challenging conditions leads to oxidative stress and cellular damage. Ischemic conditions switch complex I from rapid, reversible catalysis into a dormant state that protects upon reoxygenation, but the molecular basis for the switch is unknown. We combined precise biochemical definition of complex I catalysis with high-resolution cryo-electron microscopy structures in the phospholipid bilayer of coupled vesicles to reveal the mechanism of the transition into the dormant state, modulated by membrane interactions. By implementing a versatile membrane system to unite structure and function, attributing catalytic and regulatory properties to specific structural states, we define how a conformational switch in complex I controls its physiological roles.

Structure-guided mutagenesis of OSCAs reveals differential activation to mechanical stimuli

The dimeric two-pore OSCA/TMEM63 family has recently been identified as mechanically activated ion channels. Previously, based on the unique features of the structure of OSCA1.2, we postulated the potential involvement of several structural elements in sensing membrane tension (Jojoa-Cruz et al., 2018). Interestingly, while OSCA1, 2, and 3 clades are activated by membrane stretch in cell-attached patches (i.e. they are stretch-activated channels), they differ in their ability to transduce membrane deformation induced by a blunt probe (poking). Here, in an effort to understand the domains contributing to mechanical signal transduction, we used cryo-electron microscopy to solve the structure of Arabidopsis thaliana (At) OSCA3.1, which, unlike AtOSCA1.2, only produced stretch- but not poke-activated currents in our initial characterization (Murthy et al., 2018). Mutagenesis and electrophysiological assessment of conserved and divergent putative mechanosensitive features of OSCA1.2 reveal a selective disruption of the macroscopic currents elicited by poking without considerable effects on stretch-activated currents (SAC). Our results support the involvement of the amphipathic helix and lipid-interacting residues in the membrane fenestration in the response to poking. Our findings position these two structural elements as potential sources of functional diversity within the family.

Cryo-EM Map Anisotropy Can Be Attenuated by Map Post-Processing and a New Method for Its Estimation

One of the most important challenges in cryogenic electron microscopy (cryo-EM) is the substantial number of samples that exhibit preferred orientations, which leads to an uneven coverage of the projection sphere. As a result, the overall quality of the reconstructed maps can be severely affected, as manifested by the presence of anisotropy in the map resolution. Several methods have been proposed to measure the directional resolution of maps in tandem with experimental protocols to address the problem of preferential orientations in cryo-EM. Following these works, in this manuscript we identified one potential limitation that may affect most of the existing methods and we proposed an alternative approach to evaluate the presence of preferential orientations in cryo-EM reconstructions. In addition, we also showed that some of the most recently proposed cryo-EM map post-processing algorithms can attenuate map anisotropy, thus offering alternative visualization opportunities for cases affected by moderate levels of preferential orientations.

DeepETPicker: Fast and accurate 3D particle picking for cryo-electron tomography using weakly supervised deep learning

To solve three-dimensional structures of biological macromolecules in situ, large numbers of particles often need to be picked from cryo-electron tomograms. However, adoption of automated particle-picking methods remains limited because of their technical limitations. To overcome the limitations, we develop DeepETPicker, a deep learning model for fast and accurate picking of particles from cryo-electron tomograms. Training of DeepETPicker requires only weak supervision with low numbers of simplified labels, reducing the burden of manual annotation. The simplified labels combined with the customized and lightweight model architecture of DeepETPicker and accelerated pooling enable substantial performance improvement. When tested on simulated and real tomograms, DeepETPicker outperforms the competing state-of-the-art methods by achieving the highest overall accuracy and speed, which translate into higher authenticity and coordinates accuracy of picked particles and higher resolutions of final reconstruction maps. DeepETPicker is provided in open source with a user-friendly interface to support cryo-electron tomography in situ.

Structural and functional insights into tRNA recognition by human tRNA guanine transglycosylase

Eukaryotic tRNA guanine transglycosylase (TGT) is an RNA-modifying enzyme which catalyzes the base exchange of the genetically encoded guanine 34 of tRNAsAsp,Asn,His,Tyr for queuine, a hypermodified 7-deazaguanine derivative. Eukaryotic TGT is a heterodimer comprised of a catalytic and a non-catalytic subunit. While binding of the tRNA anticodon loop to the active site is structurally well understood, the contribution of the non-catalytic subunit to tRNA binding remained enigmatic, as no complex structure with a complete tRNA was available. Here, we report a cryo-EM structure of eukaryotic TGT in complex with a complete tRNA, revealing the crucial role of the non-catalytic subunit in tRNA binding. We decipher the functional significance of these additional tRNA-binding sites, analyze solution state conformation, flexibility, and disorder of apo TGT, and examine conformational transitions upon tRNA binding.

Structure-guided mutagenesis of OSCAs reveals differential activation to mechanical stimuli

The dimeric two-pore OSCA/TMEM63 family has recently been identified as mechanically activated ion channels. Previously, based on the unique features of the structure of OSCA1.2, we postulated the potential involvement of several structural elements in sensing membrane tension1. Interestingly, while OSCA1, 2, and 3 clades are activated by membrane stretch in cell-attached patches (i.e., they are stretch-activated channels), they differ in their ability to transduce membrane deformation induced by a blunt probe (poking). In an effort to understand the domains contributing to mechanical signal transduction, we used cryo-electron microscopy to solve the structure of Arabidopsis thaliana (At) OSCA3.1, which, unlike AtOSCA1.2, only produced stretch- but not poke-activated currents in our initial characterization2. Mutagenesis and electrophysiological assessment of conserved and divergent putative mechanosensitive features of OSCA1.2 reveal a selective disruption of the macroscopic currents elicited by poking without considerable effects on stretch-activated currents (SAC). Our results support the involvement of the amphipathic helix and lipid-interacting residues in the membrane fenestration in the response to poking. Our findings position these two structural elements as potential sources of functional diversity within the family.

Community recommendations on cryoEM data archiving and validation

In January 2020, a workshop was held at EMBL-EBI (Hinxton, UK) to discuss data requirements for the deposition and validation of cryoEM structures, with a focus on single-particle analysis. The meeting was attended by 47 experts in data processing, model building and refinement, validation, and archiving of such structures. This report describes the workshop's motivation and history, the topics discussed, and the resulting consensus recommendations. Some challenges for future methods-development efforts in this area are also highlighted, as is the implementation to date of some of the recommendations.

Structure of mechanically activated ion channel OSCA2.3 reveals mobile elements in the transmembrane domain

Members of the OSCA/TMEM63 family are mechanically activated ion channels and structures of some OSCA members have revealed the architecture of these channels and structural features that are potentially involved in mechanosensation. However, these structures are all in a similar state and information about the motion of different elements of the structure is limited, preventing a deeper understanding of how these channels work. Here, we used cryoelectron microscopy to determine high-resolution structures of Arabidopsis thaliana OSCA1.2 and OSCA2.3 in peptidiscs. The structure of OSCA1.2 matches previous structures of the same protein in different environments. Yet, in OSCA2.3, the TM6a-TM7 linker adopts a different conformation that constricts the pore on its cytoplasmic side. Furthermore, coevolutionary sequence analysis uncovered a conserved interaction between the TM6a-TM7 linker and the beam-like domain (BLD). Our results reveal conformational heterogeneity and differences in conserved interactions between the TMD and BLD among members of the OSCA family.

A proteolytic AAA+ machine poised to unfold a protein substrate

AAA+ proteolytic machines unfold proteins prior to degradation. Cryo-EM of a ClpXP-substrate complex reveals a postulated but heretofore unseen intermediate in substrate unfolding/degradation. The natively folded substrate is drawn tightly against the ClpX channel by interactions between axial pore loops and the substrate degron tail, and by contacts with the native substrate that are, in part, enabled by movement of one ClpX subunit out of the typically observed hexameric spiral.

Local defocus estimation in single particle analysis in cryo-electron microscopy

Single Particle analysis (SPA) aims to determine the three-dimensional structure of proteins and macromolecular complexes. The current state of the art has allowed us to achieve near-atomic and even atomic resolutions. To obtain high-resolution structures, a set of well-defined image processing steps is required. A critical one is the estimation of the Contrast Transfer Function (CTF), which considers the sample defocus and aberrations of the microscope. Defocus is usually globally estimated; in this case, it is the same for all the particles in each micrograph. But proteins are ice-embedded at different heights, suggesting that defocus should be measured in a local (per particle) manner. There are four state-of-the-art programs to estimate local defocus (Gctf, Relion, CryoSPARC, and Xmipp). In this work, we have compared the results of these software packages to check whether the resolution improves. We have used the Scipion framework and developed a specific program to analyze local defocus. The results produced by different programs do not show a clear consensus using the current test datasets in this study.

Cryo-EM of a heterogeneous biochemical fraction elucidates multiple protein complexes from a multicellular thermophilic eukaryote

Biomolecular complexes and their interactions govern cellular structure and function. Understanding their architecture is a prerequisite for dissecting the cell's inner workings, but their higher-order assembly is often transient and challenging for structural analysis. Here, we performed cryo-EM on a single, highly heterogeneous biochemical fraction derived from Chaetomium thermophilum cell extracts to visualize the biomolecular content of the multicellular eukaryote. After cryo-EM single-particle image processing, results showed that a simultaneous three-dimensional structural characterization of multiple chemically diverse biomacromolecules is feasible. Namely, the thermophilic, eukaryotic complexes of (a) ATP citrate-lyase, (b) Hsp90, (c) 20S proteasome, (d) Hsp60 and (e) UDP-glucose pyrophosphorylase were characterized. In total, all five complexes have been structurally dissected in a thermophilic eukaryote in a total imaged sample area of 190.64 μm2, and two, in particular, 20S proteasome and Hsp60, exhibit side-chain resolution features. The C. thermophilum Hsp60 near-atomic model was resolved at 3.46 Å (FSC = 0.143) and shows a hinge-like conformational change of its equatorial domain, highly similar to the one previously shown for its bacterial orthologue, GroEL. This work demonstrates that cryo-EM of cell extracts will greatly accelerate the structural analysis of cellular complexes and provide unprecedented opportunities to annotate architectures of biomolecules in a holistic approach.

A new algorithm for particle weighted subtraction to decrease signals from unwanted components in single particle analysis

Single particle analysis (SPA) in cryo-electron microscopy (cryo-EM) is highly used to obtain the near-atomic structure of biological macromolecules. The current methods allow users to produce high-resolution maps from many samples. However, there are still challenging cases that require extra processing to obtain high resolution. This is the case when the macromolecule of the sample is composed of different components and we want to focus just on one of them. For example, if the macromolecule is composed of several flexible subunits and we are interested in a specific one, if it is embedded in a viral capsid environment, or if it has additional components to stabilize it, such as nanodiscs. The signal from these components, which in principle we are not interested in, can be removed from the particles using a projection subtraction method. Currently, there are two projection subtraction methods used in practice and both have some limitations. In fact, after evaluating their results, we consider that the problem is still open to new solutions, as they do not fully remove the signal of the components that are not of interest. Our aim is to develop a new and more precise projection subtraction method, improving the performance of state-of-the-art methods. We tested our algorithm with data from public databases and an in-house data set. In this work, we show that the performance of our algorithm improves the results obtained by others, including the localization of small ligands, such as drugs, whose binding location is unknown a priori.

A closed translocation channel in the substrate-free AAA+ ClpXP protease diminishes rogue degradation

AAA+ proteases degrade intracellular proteins in a highly specific manner. E. coli ClpXP, for example, relies on a C-terminal ssrA tag or other terminal degron sequences to recognize proteins, which are then unfolded by ClpX and subsequently translocated through its axial channel and into the degradation chamber of ClpP for proteolysis. Prior cryo-EM structures reveal that the ssrA tag initially binds to a ClpX conformation in which the axial channel is closed by a pore-2 loop. Here, we show that substrate-free ClpXP has a nearly identical closed-channel conformation. We destabilize this closed-channel conformation by deleting residues from the ClpX pore-2 loop. Strikingly, open-channel ClpXP variants degrade non-native proteins lacking degrons faster than the parental enzymes in vitro but degraded GFP-ssrA more slowly. When expressed in E. coli, these open channel variants behave similarly to the wild-type enzyme in assays of filamentation and phage-Mu plating but resulted in reduced growth phenotypes at elevated temperatures or when cells were exposed to sub-lethal antibiotic concentrations. Thus, channel closure is an important determinant of ClpXP degradation specificity.

Structure of the Drosophila melanogaster Flight Muscle Myosin Filament at 4.7 Å Resolution Reveals New Details of Non-Myosin Proteins

Striated muscle thick filaments are composed of myosin II and several non-myosin proteins which define the filament length and modify its function. Myosin II has a globular N-terminal motor domain comprising its catalytic and actin-binding activities and a long α-helical, coiled tail that forms the dense filament backbone. Myosin alone polymerizes into filaments of irregular length, but striated muscle thick filaments have defined lengths that, with thin filaments, define the sarcomere structure. The motor domain structure and function are well understood, but the myosin filament backbone is not. Here we report on the structure of the flight muscle thick filaments from Drosophila melanogaster at 4.7 Å resolution, which eliminates previous ambiguities in non-myosin densities. The full proximal S2 region is resolved, as are the connecting densities between the Ig domains of stretchin-klp. The proteins, flightin, and myofilin are resolved in sufficient detail to build an atomic model based on an AlphaFold prediction. Our results suggest a method by which flightin and myofilin cooperate to define the structure of the thick filament and explains a key myosin mutation that affects flightin incorporation. Drosophila is a genetic model organism for which our results can define strategies for functional testing.

Hydrophobic interactions dominate the recognition of a KRAS G12V neoantigen

Specificity remains a major challenge to current therapeutic strategies for cancer. Mutation associated neoantigens (MANAs) are products of genetic alterations, making them highly specific therapeutic targets. MANAs are HLA-presented (pHLA) peptides derived from intracellular mutant proteins that are otherwise inaccessible to antibody-based therapeutics. Here, we describe the cryo-EM structure of an antibody-MANA pHLA complex. Specifically, we determine a TCR mimic (TCRm) antibody bound to its MANA target, the KRASG12V peptide presented by HLA-A*03:01. Hydrophobic residues appear to account for the specificity of the mutant G12V residue. We also determine the structure of the wild-type G12 peptide bound to HLA-A*03:01, using X-ray crystallography. Based on these structures, we perform screens to validate the key residues required for peptide specificity. These experiments led us to a model for discrimination between the mutant and the wild-type peptides presented on HLA-A*03:01 based exclusively on hydrophobic interactions.

Scipion3: A workflow engine for cryo-electron microscopy image processing and structural biology

Image-processing pipelines require the design of complex workflows combining many different steps that bring the raw acquired data to a final result with biological meaning. In the image-processing domain of cryo-electron microscopy single-particle analysis (cryo-EM SPA), hundreds of steps must be performed to obtain the three-dimensional structure of a biological macromolecule by integrating data spread over thousands of micrographs containing millions of copies of allegedly the same macromolecule. The execution of such complicated workflows demands a specific tool to keep track of all these steps performed. Additionally, due to the extremely low signal-to-noise ratio (SNR), the estimation of any image parameter is heavily affected by noise resulting in a significant fraction of incorrect estimates. Although low SNR and processing millions of images by hundreds of sequential steps requiring substantial computational resources are specific to cryo-EM, these characteristics may be shared by other biological imaging domains. Here, we present Scipion, a Python generic open-source workflow engine specifically adapted for image processing. Its main characteristics are: (a) interoperability, (b) smart object model, (c) gluing operations, (d) comparison operations, (e) wide set of domain-specific operations, (f) execution in streaming, (g) smooth integration in high-performance computing environments, (h) execution with and without graphical capabilities, (i) flexible visualization, (j) user authentication and private access to private data, (k) scripting capabilities, (l) high performance, (m) traceability, (n) reproducibility, (o) self-reporting, (p) reusability, (q) extensibility, (r) software updates, and (s) non-restrictive software licensing.

Local heterogeneity analysis of crystallographic and cryo-EM maps using shell-approximation

In X-ray crystallography and cryo-EM, experimental maps can be heterogeneous, showing different level of details in different regions. In this work we interpret heterogeneity in terms of two parameters, assigned individually for each atom, combining the conventional atomic displacement parameter with the resolution of the atomic image in the map. We propose a local real-space procedure to estimate the values of these heterogeneity parameters, assuming that a fragment of the density map and atomic positions are given. The procedure is based on an analytic representation of the atomic image, as a function of the inhomogeneity parameters and atomic coordinates. In this article, we report the results of the tests both with maps simulated and those derived from experimental data. For simulated maps containing regions with different resolutions, the method determines the local map resolution around the atomic centers and the values of the displacement parameter with reasonable accuracy. For experimental maps, obtained as a Fourier synthesis of a given global resolution, estimated values of the local resolution are close to the global one, and the values of the estimated displacement parameters are close to the respective values of the closest atoms in the refined model. Shown successful applications of the proposed method to experimental crystallographic and cryo-EM maps can be seen as a practical proof of method.

Allosteric activation of cell wall synthesis during bacterial growth

The peptidoglycan (PG) cell wall protects bacteria against osmotic lysis and determines cell shape, making this structure a key antibiotic target. Peptidoglycan is a polymer of glycan chains connected by peptide crosslinks, and its synthesis requires precise spatiotemporal coordination between glycan polymerization and crosslinking. However, the molecular mechanism by which these reactions are initiated and coupled is unclear. Here we use single-molecule FRET and cryo-EM to show that an essential PG synthase (RodA-PBP2) responsible for bacterial elongation undergoes dynamic exchange between closed and open states. Structural opening couples the activation of polymerization and crosslinking and is essential in vivo. Given the high conservation of this family of synthases, the opening motion that we uncovered likely represents a conserved regulatory mechanism that controls the activation of PG synthesis during other cellular processes, including cell division.

Improvement of cryo-EM maps by simultaneous local and non-local deep learning

Cryo-EM has emerged as the most important technique for structure determination of macromolecular complexes. However, raw cryo-EM maps often exhibit loss of contrast at high resolution and heterogeneity over the entire map. As such, various post-processing methods have been proposed to improve cryo-EM maps. Nevertheless, it is still challenging to improve both the quality and interpretability of EM maps. Addressing the challenge, we present a three-dimensional Swin-Conv-UNet-based deep learning framework to improve cryo-EM maps, named EMReady, by not only implementing both local and non-local modeling modules in a multiscale UNet architecture but also simultaneously minimizing the local smooth L1 distance and maximizing the non-local structural similarity between processed experimental and simulated target maps in the loss function. EMReady was extensively evaluated on diverse test sets of 110 primary cryo-EM maps and 25 pairs of half-maps at 3.0-6.0 Å resolutions, and compared with five state-of-the-art map post-processing methods. It is shown that EMReady can not only robustly enhance the quality of cryo-EM maps in terms of map-model correlations, but also improve the interpretability of the maps in automatic de novo model building.

Quantitative analysis of protein dynamics using a deep learning technique combined with experimental cryo-EM density data and MD simulations

Protein functions associated with biological activity are precisely regulated by both tertiary structure and dynamic behavior. Thus, elucidating the high-resolution structures and quantitative information on in-solution dynamics is essential for understanding the molecular mechanisms. The main experimental approaches for determining tertiary structures include nuclear magnetic resonance (NMR), X-ray crystallography, and cryogenic electron microscopy (cryo-EM). Among these procedures, recent remarkable advances in the hardware and analytical techniques of cryo-EM have increasingly determined novel atomic structures of macromolecules, especially those with large molecular weights and complex assemblies. In addition to these experimental approaches, deep learning techniques, such as AlphaFold 2, accurately predict structures from amino acid sequences, accelerating structural biology research. Meanwhile, the quantitative analyses of the protein dynamics are conducted using experimental approaches, such as NMR and hydrogen-deuterium mass spectrometry, and computational approaches, such as molecular dynamics (MD) simulations. Although these procedures can quantitatively explore dynamic behavior at high resolution, the fundamental difficulties, such as signal crowding and high computational cost, greatly hinder their application to large and complex biological macromolecules. In recent years, machine learning techniques, especially deep learning techniques, have been actively applied to structural data to identify features that are difficult for humans to recognize from big data. Here, we review our approach to accurately estimate dynamic properties associated with local fluctuations from three-dimensional cryo-EM density data using a deep learning technique combined with MD simulations.

ZART: A novel multiresolution reconstruction algorithm with motion-blur correction for single particle analysis

One of the main purposes of CryoEM Single Particle Analysis is to reconstruct the three-dimensional structure of a macromolecule thanks to the acquisition of many particle images representing different poses of the sample. By estimating the orientation of each projected particle, it is possible to recover the underlying 3D volume by multiple 3D reconstruction methods, usually working either in Fourier or in real space. However, the reconstruction from the projected images works under the assumption that all particles in the dataset correspond to the same conformation of the macromolecule. Although this requisite holds for some macromolecules, it is not true for flexible specimens, leading to motion-induced artefacts in the reconstructed CryoEM maps. In this work, we introduce a new Algebraic Reconstruction Technique called ZART, which is able to include continuous flexibility information during the reconstruction process to improve local resolution and reduce motion blurring. The conformational changes are modelled through Zernike3D polynomials. Our implementation allows for a multiresolution description of the macromolecule adapting itself to the local resolution of the reconstructed map. In addition, ZART has also proven to be a useful algorithm in cases where flexibility is not so dominant, as it improves the overall aspect of the reconstructed maps by improving their local and global resolution.

CryoRes: Local Resolution Estimation of Cryo-EM Density Maps by Deep Learning

Recent progress in cryo-EM research has ignited a revolution in biological macromolecule structure determination. Resolution is an essential parameter for quality assessment of a cryo-EM density map, and it is known that resolution varies in different regions of a map. Currently available methods for local resolution estimation require manual adjustment of parameters and in some cases necessitate acquisition or de novo generation of so-called "half maps". Here, we developed CryoRes, a deep-learning algorithm to estimate local resolution directly from a single final cryo-EM density map, specifically by learning resolution-aware patterns of density map voxels through supervised training on a large dataset comprising 1,174 experimental cryo-EM density maps. CryoRes significantly outperforms all of the state-of-the-art competing resolution estimation methods, achieving an average RMSE of 2.26 Å for local resolution estimation relative to the currently most reliable FSC-based method blocres, yet requiring only the single final map as input. Further, CryoRes is able to generate a molecular mask for each map, with accuracy 12.12% higher than the masks generated by ResMap. CryoRes is ultra-fast, fully automatic, parameter-free, applicable to cryo-EM subtomogram data, and freely available at https://cryores.zhanglab.net.

Automatic and accurate ligand structure determination guided by cryo-electron microscopy maps

Advances in cryo-electron microscopy (cryoEM) and deep-learning guided protein structure prediction have expedited structural studies of protein complexes. However, methods for accurately determining ligand conformations are lacking. In this manuscript, we develop EMERALD, a tool for automatically determining ligand structures guided by medium-resolution cryoEM density. We show this method is robust at predicting ligands along with surrounding side chains in maps as low as 4.5 Å local resolution. Combining this with a measure of placement confidence and running on all protein/ligand structures in the EMDB, we show that 57% of ligands replicate the deposited model, 16% confidently find alternate conformations, 22% have ambiguous density where multiple conformations might be present, and 5% are incorrectly placed. For five cases where our approach finds an alternate conformation with high confidence, high-resolution crystal structures validate our placement. EMERALD and the resulting analysis should prove critical in using cryoEM to solve protein-ligand complexes.

Cryo-electron Microscopy of Protein Cages

Protein cages are one of the most widely studied objects in the field of cryogenic electron microscopy-encompassing natural and synthetic constructs, from enzymes assisting protein folding such as chaperonin to virus capsids. Tremendous diversity of morphology and function is demonstrated by the structure and role of proteins, some of which are nearly ubiquitous, while others are present in few organisms. Protein cages are often highly symmetrical, which helps improve the resolution obtained by cryo-electron microscopy (cryo-EM). Cryo-EM is the study of vitrified samples using an electron probe to image the subject. A sample is rapidly frozen in a thin layer on a porous grid, attempting to keep the sample as close to a native state as possible. This grid is kept at cryogenic temperatures throughout imaging in an electron microscope. Once image acquisition is complete, a variety of software packages may be employed to carry out analysis and reconstruction of three-dimensional structures from the two-dimensional micrograph images. Cryo-EM can be used on samples that are too large or too heterogeneous to be amenable to other structural biology techniques like NMR or X-ray crystallography. In recent years, advances in both hardware and software have provided significant improvements to the results obtained using cryo-EM, recently demonstrating true atomic resolution from vitrified aqueous samples. Here, we review these advances in cryo-EM, especially in that of protein cages, and introduce several tips for situations we have experienced.

Structure of the Flight Muscle Thick Filament from the Bumble Bee, Bombus ignitus, at 6 Å Resolution

Four insect orders have flight muscles that are both asynchronous and indirect; they are asynchronous in that the wingbeat frequency is decoupled from the frequency of nervous stimulation and indirect in that the muscles attach to the thoracic exoskeleton instead of directly to the wing. Flight muscle thick filaments from two orders, Hemiptera and Diptera, have been imaged at a subnanometer resolution, both of which revealed a myosin tail arrangement referred to as “curved molecular crystalline layers”. Here, we report a thick filament structure from the indirect flight muscles of a third insect order, Hymenoptera, the Asian bumble bee Bombus ignitus. The myosin tails are in general agreement with previous determinations from Lethocerus indicus and Drosophila melanogaster. The Skip 2 region has the same unusual structure as found in Lethocerus indicus thick filaments, an α-helix discontinuity is also seen at Skip 4, but the orientation of the Skip 1 region on the surface of the backbone is less angled with respect to the filament axis than in the other two species. The heads are disordered as in Drosophila, but we observe no non-myosin proteins on the backbone surface that might prohibit the ordering of myosin heads onto the thick filament backbone. There are strong structural similarities among the three species in their non-myosin proteins within the backbone that suggest how one previously unassigned density in Lethocerus might be assigned. Overall, the structure conforms to the previously observed pattern of high similarity in the myosin tail arrangement, but differences in the non-myosin proteins.

Image processing tools for the validation of CryoEM maps

The number of maps deposited in public databases (Electron Microscopy Data Bank, EMDB) determined by cryo-electron microscopy has quickly grown in recent years. With this rapid growth, it is critical to guarantee their quality. So far, map validation has primarily focused on the agreement between maps and models. From the image processing perspective, the validation has been mostly restricted to using two half-maps and the measurement of their internal consistency. In this article, we suggest that map validation can be taken much further from the point of view of image processing if 2D classes, particles, angles, coordinates, defoci, and micrographs are also provided. We present a progressive validation scheme that qualifies a result validation status from 0 to 5 and offers three optional qualifiers (A, W, and O) that can be added. The simplest validation state is 0, while the most complete would be 5AWO. This scheme has been implemented in a website https://biocomp.cnb.csic.es/EMValidationService/ to which reconstructed maps and their ESI can be uploaded.

Analytic modeling of inhomogeneous-resolution maps in cryo-electron microscopy and crystallography

Refinement of macromolecular atomic models versus experimental maps in crystallography and cryo-electron microscopy is a critical step in structure solution. For an appropriate comparison, model maps should mimic the imperfections in the experimental maps, mainly atomic disorder and limited resolution, which are often inhomogeneous over the molecular region. In the suggested method, these model maps are calculated as the sum of atomic contributions expressed through a specifically designed function describing a solitary spherical wave. Thanks to this function, atomic contributions are analytically expressed through their atomic displacement parameter and local resolution, a value now associated with each atom. Such a full analytic dependence of inhomogeneous-resolution map values on model parameters permits the refinement of all of these parameters together.

Cryo-EM structure-based selection of computed ligand poses enables design of MTA-synergic PRMT5 inhibitors of better potency

Projected potential of 2.5-4.0 Å cryo-EM structures for structure-based drug design is not well realized yet. Here we show that a 3.1 Å structure of PRMT5 is suitable for selecting computed poses of a chemical inhibitor and its analogs for enhanced potency. PRMT5, an oncogenic target for various cancer types, has many inhibitors manifesting little cooperativity with MTA, a co-factor analog accumulated in MTAP-/- cells. To achieve MTA-synergic inhibition, a pharmacophore from virtual screen leads to a specific inhibitor (11-2 F). Cryo-EM structures of 11-2 F / MTA-bound human PRMT5/MEP50 complex and its apo form resolved at 3.1 and 3.2 Å respectively show that 11-2 F in the catalytic pocket shifts the cofactor-binding pocket away by ~2.0 Å, contributing to positive cooperativity. Computational analysis predicts subtype specificity of 11-2 F among PRMTs. Structural analysis of ligands in the binding pockets is performed to compare poses of 11-2 F and its redesigned analogs and identifies three new analogs predicted to have significantly better potency. One of them, after synthesis, is ~4 fold more efficient in inhibiting PRMT5 catalysis than 11-2 F, with strong MTA-synergy. These data suggest the feasibility of employing near-atomic resolution cryo-EM structures and computational analysis of ligand poses for small molecule therapeutics.

Structure of the TnsB transposase-DNA complex of type V-K CRISPR-associated transposon

CRISPR-associated transposons (CASTs) are mobile genetic elements that co-opted CRISPR-Cas systems for RNA-guided transposition. Here we present the 2.4 Å cryo-EM structure of the Scytonema hofmannii (sh) TnsB transposase from Type V-K CAST, bound to the strand transfer DNA. The strand transfer complex displays an intertwined pseudo-symmetrical architecture. Two protomers involved in strand transfer display a catalytically competent active site composed by DDE residues, while other two, which play a key structural role, show active sites where the catalytic residues are not properly positioned for phosphodiester hydrolysis. Transposon end recognition is accomplished by the NTD1/2 helical domains. A singular in trans association of NTD1 domains of the catalytically competent subunits with the inactive DDE domains reinforces the assembly. Collectively, the structural features suggest that catalysis is coupled to protein-DNA assembly to secure proper DNA integration. DNA binding residue mutants reveal that lack of specificity decreases activity, but it could increase transposition in some cases. Our structure sheds light on the strand transfer reaction of DDE transposases and offers new insights into CAST transposition.

The cryo-EM structure of the type VK CRISPR-associated TnsB transposase sheds light onto RNA-guided transposition, providing new possibilities to redesign CRISPR-associated transposon systems.

Emerging Themes in CryoEM─Single Particle Analysis Image Processing

Cryo-electron microscopy (CryoEM) has become a vital technique in structural biology. It is an interdisciplinary field that takes advantage of advances in biochemistry, physics, and image processing, among other disciplines. Innovations in these three basic pillars have contributed to the boosting of CryoEM in the past decade. This work reviews the main contributions in image processing to the current reconstruction workflow of single particle analysis (SPA) by CryoEM. Our review emphasizes the time evolution of the algorithms across the different steps of the workflow differentiating between two groups of approaches: analytical methods and deep learning algorithms. We present an analysis of the current state of the art. Finally, we discuss the emerging problems and challenges still to be addressed in the evolution of CryoEM image processing methods in SPA.

Architecture of the yeast Pol III pre-termination complex and pausing mechanism on poly(dT) termination signals

RNA polymerase (Pol) III is specialized to transcribe short, abundant RNAs, for which it terminates transcription on polythymine (dT) stretches on the non-template (NT) strand. When Pol III reaches the termination signal, it pauses and forms the pre-termination complex (PTC). Here, we report cryoelectron microscopy (cryo-EM) structures of the yeast Pol III PTC and complementary functional states at resolutions of 2.7-3.9 Å. Pol III recognizes the poly(dT) termination signal with subunit C128 that forms a hydrogen-bond network with the NT strand and, thereby, induces pausing. Mutating key interacting residues interferes with transcription termination in vitro, impairs yeast growth, and causes global termination defects in vivo, confirming our structural results. Additional cryo-EM analysis reveals that C53-C37, a Pol III subcomplex and key termination factor, participates indirectly in Pol III termination. We propose a mechanistic model of Pol III transcription termination and rationalize why Pol III, unlike Pol I and Pol II, terminates on poly(dT) signals.

Cryo-electron microscopy and image classification reveal the existence and structure of the coxsackievirus A6 virion

Coxsackievirus A6 (CV-A6) has recently overtaken enterovirus A71 and CV-A16 as the primary causative agent of hand, foot, and mouth disease worldwide. Virions of CV-A6 were not identified in previous structural studies, and it was speculated that the virus is unique among enteroviruses in using altered particles with expanded capsids to infect cells. In contrast, the virions of other enteroviruses are required for infection. Here we used cryo-electron microscopy (cryo-EM) to determine the structures of the CV-A6 virion, altered particle, and empty capsid. We show that the CV-A6 virion has features characteristic of virions of other enteroviruses, including a compact capsid, VP4 attached to the inner capsid surface, and fatty acid-like molecules occupying the hydrophobic pockets in VP1 subunits. Furthermore, we found that in a purified sample of CV-A6, the ratio of infectious units to virions is 1 to 500. Therefore, it is likely that virions of CV-A6 initiate infection, like those of other enteroviruses. Our results provide evidence that future vaccines against CV-A6 should target its virions instead of the antigenically distinct altered particles. Furthermore, the structure of the virion provides the basis for the rational development of capsid-binding inhibitors that block the genome release of CV-A6.

A cryo-EM structure for the three conformers of coxsackievirus A6 provides insight into the infection process of this enterovirus, which is responsible for numerous cases of hand, foot, and mouth disease.

Higher resolution in cryo-EM by the combination of macromolecular prior knowledge and image-processing tools

Single-particle cryo-electron microscopy has become a powerful technique for the 3D structure determination of biological molecules. The last decade has seen an astonishing development of both hardware and software, and an exponential growth of new structures obtained at medium-high resolution. However, the knowledge accumulated in this field over the years has hardly been utilized as feedback in the reconstruction of new structures. In this context, this article explores the use of the deep-learning approach deepEMhancer as a regularizer in the RELION refinement process. deepEMhancer introduces prior information derived from macromolecular structures, and contributes to noise reduction and signal enhancement, as well as a higher degree of isotropy. These features have a direct effect on image alignment and reduction of overfitting during iterative refinement. The advantages of this combination are demonstrated for several membrane proteins, for which it is especially useful because of their high disorder and flexibility.

Artificial Intelligence in Cryo-Electron Microscopy

Cryo-electron microscopy (cryo-EM) has become an unrivaled tool for determining the structure of macromolecular complexes. The biological function of macromolecular complexes is inextricably tied to the flexibility of these complexes. Single particle cryo-EM can reveal the conformational heterogeneity of a biochemically pure sample, leading to well-founded mechanistic hypotheses about the roles these complexes play in biology. However, the processing of increasingly large, complex datasets using traditional data processing strategies is exceedingly expensive in both user time and computational resources. Current innovations in data processing capitalize on artificial intelligence (AI) to improve the efficiency of data analysis and validation. Here, we review new tools that use AI to automate the data analysis steps of particle picking, 3D map reconstruction, and local resolution determination. We discuss how the application of AI moves the field forward, and what obstacles remain. We also introduce potential future applications of AI to use cryo-EM in understanding protein communities in cells.

ScipionTomo: Towards cryo-electron tomography software integration, reproducibility, and validation

Image processing in cryogenic electron tomography (cryoET) is currently at a similar state as Single Particle Analysis (SPA) in cryogenic electron microscopy (cryoEM) was a few years ago. Its data processing workflows are far from being well defined and the user experience is still not smooth. Moreover, file formats of different software packages and their associated metadata are not standardized, mainly since different packages are developed by different groups, focusing on different steps of the data processing pipeline.

The Scipion framework, originally developed for SPA (de la Rosa-Trevín et al., 2016), has a generic python workflow engine that gives it the versatility to be extended to other fields, as demonstrated for model building (Martínez et al., 2020). In this article, we provide an extension of Scipion based on a set of tomography plugins (referred to as ScipionTomo hereafter), with a similar purpose: to allow users to be focused on the data processing and analysis instead of having to deal with multiple software installation issues and the inconvenience of switching from one to another, converting metadata files, managing possible incompatibilities, scripting (writing a simple program in a language that the computer must convert to machine language each time the program is run), etcetera. Additionally, having all the software available in an integrated platform allows comparing the results of different algorithms trying to solve the same problem. In this way, the commonalities and differences between estimated parameters shed light on which results can be more trusted than others. ScipionTomo is developed by a collaborative multidisciplinary team composed of Scipion team engineers, structural biologists, and in some cases, the developers whose software packages have been integrated. It is open to anyone in the field willing to contribute to this project.

The result is a framework extension that combines the acquired knowledge of Scipion developers in close collaboration with third-party developers, and the on-demand design of functionalities requested by beta testers applying this solution to actual biological problems.

Cryo-EM structures show the mechanistic basis of pan-peptidase inhibition by human α2-macroglobulin

Human α₂-macroglobulin (hα₂M) is an ∼720-kDa homotetrameric particle with pan-peptidase inhibitory functions that transits between an open native conformation and a closed induced state, in which endopeptidases are trapped upon cleavage of an accessible bait region. We determined the molecular mechanism of this function through eight cryo–electron microscopy (cryo-EM) structures, which revealed that the hα₂M subunits are organized in two flexible modules that undergo independent expanded-to-compact transitions. In the induced state, a reactive thioester bond triggers covalent linking of the proteinase, and a receptor-binding domain is exposed on the tetramer surface for binding to its specific cellular receptor for internalization and clearance from circulation. These results elucidate the long-awaited molecular mechanism of a historical suicidal inhibitory trap.

Human α₂-macroglobulin (hα₂M) is a multidomain protein with a plethora of essential functions, including transport of signaling molecules and endopeptidase inhibition in innate immunity. Here, we dissected the molecular mechanism of the inhibitory function of the ∼720-kDa hα₂M tetramer through eight cryo–electron microscopy (cryo-EM) structures of complexes from human plasma. In the native complex, the hα₂M subunits are organized in two flexible modules in expanded conformation, which enclose a highly porous cavity in which the proteolytic activity of circulating plasma proteins is tested. Cleavage of bait regions exposed inside the cavity triggers rearrangement to a compact conformation, which closes openings and entraps the prey proteinase. After the expanded-to-compact transition, which occurs independently in the four subunits, the reactive thioester bond triggers covalent linking of the proteinase, and the receptor-binding domain is exposed on the tetramer surface for receptor-mediated clearance from circulation. These results depict the molecular mechanism of a unique suicidal inhibitory trap.

Validation analysis of EMDB entries

The Electron Microscopy Data Bank (EMDB) is the central archive of the electron cryo-microscopy (cryo-EM) community for storing and disseminating volume maps and tomograms. With input from the community, EMDB has developed new resources for the validation of cryo-EM structures, focusing on the quality of the volume data alone and that of the fit of any models, themselves archived in the Protein Data Bank (PDB), to the volume data. Based on recommendations from community experts, the validation resources are developed in a three-tiered system. Tier 1 covers an extensive and evolving set of validation metrics, including tried and tested metrics as well as more experimental ones, which are calculated for all EMDB entries and presented in the Validation Analysis (VA) web resource. This system is particularly useful for cryo-EM experts, both to validate individual structures and to assess the utility of new validation metrics. Tier 2 comprises a subset of the validation metrics covered by the VA resource that have been subjected to extensive testing and are considered to be useful for specialists as well as nonspecialists. These metrics are presented on the entry-specific web pages for the entire archive on the EMDB website. As more experience is gained with the metrics included in the VA resource, it is expected that consensus will emerge in the community regarding a subset that is suitable for inclusion in the tier 2 system. Tier 3, finally, consists of the validation reports and servers that are produced by the Worldwide Protein Data Bank (wwPDB) Consortium. Successful metrics from tier 2 will be proposed for inclusion in the wwPDB validation pipeline and reports. The details of the new resource are described, with an emphasis on the tier 1 system. The output of all three tiers is publicly available, either through the EMDB website (tiers 1 and 2) or through the wwPDB ftp sites (tier 3), although the content of all three will evolve over time (fastest for tier 1 and slowest for tier 3). It is our hope that these validation resources will help the cryo-EM community to obtain a better understanding of the quality and of the best ways to assess the quality of cryo-EM structures in EMDB and PDB.

Probing Structural Perturbation of Biomolecules by Extracting Cryo-EM Data Heterogeneity

Single-particle cryogenic electron microscopy (cryo-EM) has become an indispensable tool to probe high-resolution structural detail of biomolecules. It enables direct visualization of the biomolecules and opens a possibility for averaging molecular images to reconstruct a three-dimensional Coulomb potential density map. Newly developed algorithms for data analysis allow for the extraction of structural heterogeneity from a massive and low signal-to-noise-ratio (SNR) cryo-EM dataset, expanding our understanding of multiple conformational states, or further implications in dynamics, of the target biomolecule. This review provides an overview that briefly describes the workflow of single-particle cryo-EM, including imaging and data processing, and new methods developed for analyzing the data heterogeneity to understand the structural variability of biomolecules.